We revisit certain problems of pose estimation based on 3D–2D correspondences between features which may be points or lines. Specifically, we address the two previously-studied minimal problems of estimating camera extrinsics from $p \\in \\{ 1, 2 \\}$ point–point correspondences and $l=3-p$ line–line correspondences. To the best of our knowledge, all of the previously-known practical solutions to these problems required computing the roots of degree $\\ge 4$ (univariate) polynomials when $p=2$, or degree $\\ge 8$ polynomials when $p=1.$ We describe and implement two elementary solutions which reduce the degrees of the needed polynomials from $4$ to $2$ and from $8$ to $4$, respectively. We show experimentally that the resulting solvers are numerically stable and fast: when compared to the previous state-of-the art, we may obtain nearly an order of magnitude speedup. The code is available at \\url{https:\/\/github.com\/petrhruby97\/efficient\\_absolute}<\/p>\n","protected":false},"excerpt":{"rendered":"
We revisit certain problems of pose estimation based on 3D–2D correspondences between features which may be points or lines. Specifically, we address the two previously-studied minimal problems of estimating camera extrinsics from $p \\in \\{ 1, 2 \\}$ point–point correspondences and $l=3-p$ line–line correspondences. To the best of our knowledge, all of the previously-known practical 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